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Description of Statistical Computation

Author's title

Consumptieprijsindexen Kleding en Schoeisel: Spreidings -en gemiddelde graf...

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 24 Apr 2017 21:22:55 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Apr/24/t1493065538v0xn60on2m1b2n8.htm/, Retrieved Sun, 19 May 2024 01:25:06 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Sun, 19 May 2024 01:25:06 +0200
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact0

Tree of Dependent Computations

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
101.16
99.09
99.14
99.36
99.57
99.6
99.65
99.8
100.15
100.45
100.81
100.89
100.92
100.94
101.1
101.1
101.11
101.13
101.13
101.15
101.17
101.17
101.2
101.21
101.22
101.25
101.29
101.34
101.35
101.39
101.4
101.43
101.43
101.6
101.63
101.7
101.72
101.73
101.92
101.95
102.05
102.05
102.07
102.1
102.16
102.18
102.22
102.37
102.4
102.42
102.47
102.48
102.51
102.53
102.59
102.61
102.61
102.62
102.66
102.67
102.69
102.72
102.73
102.78
102.93
103
103.02
103.06
103.17
103.52
103.69
103.73

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
199.97250.7067483157519252.06999999999999
2101.1108333333330.09189503234504560.289999999999992
3101.4191666666670.1518047989020660.480000000000004
4102.0433333333330.1908989896317530.650000000000006
5102.54750.09186205072627180.269999999999996
6103.0866666666670.3720785189209721.04000000000001

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 99.9725 & 0.706748315751925 & 2.06999999999999 \tabularnewline
2 & 101.110833333333 & 0.0918950323450456 & 0.289999999999992 \tabularnewline
3 & 101.419166666667 & 0.151804798902066 & 0.480000000000004 \tabularnewline
4 & 102.043333333333 & 0.190898989631753 & 0.650000000000006 \tabularnewline
5 & 102.5475 & 0.0918620507262718 & 0.269999999999996 \tabularnewline
6 & 103.086666666667 & 0.372078518920972 & 1.04000000000001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=1

[TABLE]
[ROW][C]Standard Deviation-Mean Plot[/C][/ROW]
[ROW][C]Section[/C][C]Mean[/C][C]Standard Deviation[/C][C]Range[/C][/ROW]
[ROW][C]1[/C][C]99.9725[/C][C]0.706748315751925[/C][C]2.06999999999999[/C][/ROW]
[ROW][C]2[/C][C]101.110833333333[/C][C]0.0918950323450456[/C][C]0.289999999999992[/C][/ROW]
[ROW][C]3[/C][C]101.419166666667[/C][C]0.151804798902066[/C][C]0.480000000000004[/C][/ROW]
[ROW][C]4[/C][C]102.043333333333[/C][C]0.190898989631753[/C][C]0.650000000000006[/C][/ROW]
[ROW][C]5[/C][C]102.5475[/C][C]0.0918620507262718[/C][C]0.269999999999996[/C][/ROW]
[ROW][C]6[/C][C]103.086666666667[/C][C]0.372078518920972[/C][C]1.04000000000001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
199.97250.7067483157519252.06999999999999
2101.1108333333330.09189503234504560.289999999999992
3101.4191666666670.1518047989020660.480000000000004
4102.0433333333330.1908989896317530.650000000000006
5102.54750.09186205072627180.269999999999996
6103.0866666666670.3720785189209721.04000000000001






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha11.0318321585752
beta-0.105846971787297
S.D.0.0934932634049733
T-STAT-1.13213474353562
p-value0.32084570090579

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 11.0318321585752 \tabularnewline
beta & -0.105846971787297 \tabularnewline
S.D. & 0.0934932634049733 \tabularnewline
T-STAT & -1.13213474353562 \tabularnewline
p-value & 0.32084570090579 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]11.0318321585752[/C][/ROW]
[ROW][C]beta[/C][C]-0.105846971787297[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0934932634049733[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.13213474353562[/C][/ROW]
[ROW][C]p-value[/C][C]0.32084570090579[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha11.0318321585752
beta-0.105846971787297
S.D.0.0934932634049733
T-STAT-1.13213474353562
p-value0.32084570090579






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha110.770516478355
beta-24.3142450097977
S.D.34.8846227054096
T-STAT-0.696990339128058
p-value0.524193029010824
Lambda25.3142450097977

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 110.770516478355 \tabularnewline
beta & -24.3142450097977 \tabularnewline
S.D. & 34.8846227054096 \tabularnewline
T-STAT & -0.696990339128058 \tabularnewline
p-value & 0.524193029010824 \tabularnewline
Lambda & 25.3142450097977 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]110.770516478355[/C][/ROW]
[ROW][C]beta[/C][C]-24.3142450097977[/C][/ROW]
[ROW][C]S.D.[/C][C]34.8846227054096[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.696990339128058[/C][/ROW]
[ROW][C]p-value[/C][C]0.524193029010824[/C][/ROW]
[ROW][C]Lambda[/C][C]25.3142450097977[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&T=3

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha110.770516478355
beta-24.3142450097977
S.D.34.8846227054096
T-STAT-0.696990339128058
p-value0.524193029010824
Lambda25.3142450097977


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 12 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
(n <- length(x))
(np <- floor(n / par1))
arr <- array(NA,dim=c(par1,np))
j <- 0
k <- 1
for (i in 1:(np*par1))
{
j = j + 1
arr[j,k] <- x[i]
if (j == par1) {
j = 0
k=k+1
}
}
arr
arr.mean <- array(NA,dim=np)
arr.sd <- array(NA,dim=np)
arr.range <- array(NA,dim=np)
for (j in 1:np)
{
arr.mean[j] <- mean(arr[,j],na.rm=TRUE)
arr.sd[j] <- sd(arr[,j],na.rm=TRUE)
arr.range[j] <- max(arr[,j],na.rm=TRUE) - min(arr[,j],na.rm=TRUE)
}
arr.mean
arr.sd
arr.range
(lm1 <- lm(arr.sd~arr.mean))
(lnlm1 <- lm(log(arr.sd)~log(arr.mean)))
(lm2 <- lm(arr.range~arr.mean))
bitmap(file='test1.png')
plot(arr.mean,arr.sd,main='Standard Deviation-Mean Plot',xlab='mean',ylab='standard deviation')
dev.off()
bitmap(file='test2.png')
plot(arr.mean,arr.range,main='Range-Mean Plot',xlab='mean',ylab='range')
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Standard Deviation-Mean Plot',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Section',header=TRUE)
a<-table.element(a,'Mean',header=TRUE)
a<-table.element(a,'Standard Deviation',header=TRUE)
a<-table.element(a,'Range',header=TRUE)
a<-table.row.end(a)
for (j in 1:np) {
a<-table.row.start(a)
a<-table.element(a,j,header=TRUE)
a<-table.element(a,arr.mean[j])
a<-table.element(a,arr.sd[j] )
a<-table.element(a,arr.range[j] )
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Regression: S.E.(k) = alpha + beta * Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lm1$coefficients[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,lm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,4])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lnlm1$coefficients[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,lnlm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,4])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Lambda',header=TRUE)
a<-table.element(a,1-lnlm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')